The Tissue Doppler Imaging (TDI) technique, which is developed based on the principle of Doppler frequency shift, is an ultrasound imaging technique for detecting and analyzing the motion and function of local tissue in vivo. Presently, the TDI technique is widely applied to the clinical diagnosis of cardiac muscle disease since it can make an accurate evaluation of the local tissue function, especially the function of cardiac muscles in a local area.
Both the cardiac blood flow and muscle show the different movement in a cardiac cycle. Currently, the color flow imaging technique has been able to present the motion of blood flow quite accurately. It has been noted that the motion of cardiac muscles is just different from that of blood flow in terms of the range of velocity and amplitude. Specifically, the blood flow signals are characteristic in having high-frequency and low-amplitude, while the signals for cardiac muscles are characteristic in having low-frequency and high-amplitude. Due to the difference between them, Tissue Doppler Imaging system may be obtained, on the basis of the conventional color flow Imaging technique, only by selecting the signals with low-frequency and high-amplitude, which corresponds to the cardiac muscle motion. This may be realized by modifying a filter and a gain controller in a practical color flow imaging system,
FIG. 1 is a diagram for showing a TDI system in the prior art. As shown in FIG. 1, a transceiver unit 110 transmits ultrasound waves to a target area of interest in a human body such as the heart, and receives the echo signals returned from the targets. After being processed by a preamplifier, an analog digital converter (ADC) and a digital beam former (DBF), the received echo signals, in one path, are input into a unit 150 for non-Doppler signal processing, so as to directly display the anatomic configuration of the cardiac tissue in a display unit 160. In another path, the echo signals are input into a unit 120 for quadrature demodulating and then sent to the block of Doppler analysis. In the quadrature demodulating unit 120, the echo signals are quadrature demodulated into in-phase Doppler signal I and quadrature Doppler signal Q, which are then output to a filter 130 for obtaining the signals for cardiac muscle motion.
Subsequently, a Doppler signal processing unit 140 performs Doppler estimation on the signals output from the filter 130 in accordance with the similar manner as the Doppler flow imaging, for example, performing the autocorrelation estimation, Fast Fourier Transform (FFT), etc., so as to calculate motion parameters of the Doppler signals such as the frequency shift F, power P, variance T and so on. Wherein the frequency shift F of Doppler signals is proportional to the motion velocity V of a detected target based on the principle of Doppler effect, and thereby the velocity V is generally used to denote the frequency shift F, as shown in FIG. 1. The estimated motion parameters are then color encoded and input into a display unit 160. In the display unit 160, the encoded image of Doppler signals' motion parameters are mixed with the image of anatomic configuration for cardiac tissue, which is acquired by the non-Doppler signal processing, and at last the mixed image is presented on a screen after being converted by a Digital Scan Converter (DSC).
In the TDI system as shown in FIG. 1, in order to acquire accurate image for cardiac muscle motion, the design of the filter 130 is one of the critical steps, and also one of the challenging steps. With the rapid development of digital computer technology, researchers have proposed several methods to obtain the signals for cardiac muscle motion, for example, the method of applying a low-pass filter (LPF) to remove the blood flow signals, the method of bypassing the high-pass filter (HPF) in the conventional color flow imaging system to remove the blood flow signals, and the method of modifying the cutoff frequency of the original HPF, etc.
The main difference between the TDI systems designed according to the above methods is whether the HPF is applied. In the first method that the HPF is bypassed, the information regarding to the stationary tissue, blood flow and nonstationary cardiac muscle within a heart is all included in the extracted Doppler signals and is sent to unit 140 for Doppler estimation. Therefore, it is the image synthesizer to correctly distinguish the signals for cardiac muscle motion from other signals and display the obtained result. In this case, however, the image synthesizer can only remove blood flow signals having low-amplitude based on the signals' amplitude. For the echo signals from the stationary tissue that have relative high-amplitude, it is difficult to distinguish and remove them only based on the signals' amplitude. Consequently, by using this method, the noise caused by signals from the stationary tissue will be inevitably occurred in the images of cardiac muscle motion, thereby degrading the image quality.
The similar problem is also occurred in the second method of using a LPF to remove the blood flow information. In this method, despite the blood flow signals with high-frequency can be removed by a filter, the echo signals from the stationary tissue still exist together with the echo signals from the cardiac muscle, and they cannot be distinguished only based on the signals' amplitude. Thus, in the above two methods without a HPF, how to remove the echo signals from the stationary tissue is a problem to be resolved.
In the third method, the cutoff frequency of the HPF can be modified according to the velocity range of cardiac muscle motion (for example, being lowered appropriately), so that only the echo signals from the stationary tissue will be removed by the filter. It is obvious that the shortcomings of the above two schemes can be overcome in the third one. However, this modified HPF generally performs time domain filtering directly on the Doppler signals (I and Q) extracted from the echo signals, such as by using a Infinite Impulse Response (IIR) filter, and as a result this kind of filter needs large amounts of hardware resources when implemented in hardware,
Moreover, the Tissue Doppler Imaging system is usually used for imaging the cardiac tissue motion, thus the imaging speed needs to be fast enough so as to track the status of the cardiac tissue motion. In other words, the imaging frame rate needs to be a relatively higher value. This requirement directly results in that the pulses repetition number on each scan line in one frame is decreased, which is generally 3 in a practical system. At the same time, the pulse repetition number determines the number of samples in quadrature Doppler signals that can be used for each range cell in each imaging operation. This means that, for each range cell, only a few (for example, 3) sampling points of the Doppler signals are sent to the filter and processed. However, when filtering the finite input signals, the inherent transient response of the filter will cause the frequency characteristics of input signals to be distorted. Especially as the filter order increases, which may be helpful to acquire perfect cutoff characteristics of the filter, the duration of the filter's transient response will be increased correspondingly, which results in a seriously adverse impact on the frequency characteristics of input signals.
Therefore, although the echo signals from the stationary tissue can be removed by modifying the cutoff frequency of the HPF, the filtering performed before the Doppler estimation will directly affect the accuracy of Doppler velocity estimation, thereby degrading the image quality of Doppler tissue velocity in a TDI system.
Based on the above analysis, it is difficult for TDI systems in the prior art to achieve satisfying image quality. Therefore, a new method and apparatus used for TDI is needed to address the above issues.